A SYSTEM FOR INTEGRATED SCAT DATA COLLECTION AND MANAGEMENT: ESCAT, SCATDB, AND PHOTOLOGGER

2008 ◽  
Vol 2008 (1) ◽  
pp. 481-484 ◽  
Author(s):  
Jeffrey F. Lankford ◽  
Ian Zelo ◽  
Matt R. Stumbaugh
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Field Data ◽  
Digital Data ◽  
Handheld Devices ◽  
Handheld Computing ◽  
Field Data Collection ◽  
Digital Options ◽  
Multiple Field ◽  
Collection And Management

ABSTRACT During response, oiled shorelines must be surveyed to guide cleanup operations. The Shoreline Cleanup and Assessment Technique (SCAT) is a standard method for conducting these surveys. Multiple field teams often conduct SCAT. SCAT surveys quickly produce a large and complex dataset comprised of SCAT observations, GPS positions, and photographs. In order to guide response decision-making, SCAT field data must be processed and analyzed in a timely manner. Until recently, SCAT and GPS data were collected on standardized paper worksheets, transcribed to electronic form, and then incorporated into maps and other decision-making products. Photographs were not tightly managed alongside SCAT data. Today, with the emergence of robust handheld computing technology, the deficiencies inherent in paper data collection are no longer necessary or acceptable. Paper data collection can be slow, error prone, and lacking quality control and integration with GPS technology. Digital options are available to address these challenges. To improve methods, the Office of Response and Restoration is developing a digital field data collection and management system for SCAT data and photographs composed of: (1) specialized software for efficient SCAT data collection with GPS enabled handheld devices, (2) a relational SCAT database which expedites the synthesis of field data into decision making products, promotes community standards, and supports standard paper worksheet and digital data collection methods, and (3) an image database which allows for the processing, documenting, and sharing of large quantities of digital photographs. For this project, commonly used, readily available, and Open Source computing resources were chosen so that end-users could easily test, adopt, and improve this system.

scholarly journals Novel Approach to Support Rapid Data Collection, Management, and Visualization During the COVID-19 Outbreak Response in the World Health Organization African Region: Development of a Data Summarization and Visualization Tool

10.2196/20355 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e20355
Author(s):  
Kamran Ahmed ◽  
Muhammad Arish Bukhari ◽  
Tamayi Mlanda ◽  
Jean Paul Kimenyi ◽  
Polly Wallace ◽  
...  
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Field Data ◽  
World Health ◽  
African Region ◽  
Data Summarization ◽  
The World ◽  
Field Data Collection ◽  
Health Organization ◽  
Collection And Management

Background The COVID-19 pandemic has created unprecedented challenges to the systematic and timely sharing of COVID-19 field data collection and management. The World Health Organization (WHO) is working with health partners on the rollout and implementation of a robust electronic field data collection platform. The delay in the deployment and rollout of this electronic platform in the WHO African Region, as a consequence of the application of large-scale public health and social measures including movement restrictions and geographical area quarantine, left a gap between data collection and management. This lead to the need to develop interim data management solutions to accurately monitor the evolution of the pandemic and support the deployment of appropriate public health interventions. Objective The aim of this study is to review the design, development, and implementation of the COVID-19 Data Summarization and Visualization (DSV) tool as a rapidly deployable solution to fill this critical data collection gap as an interim solution. Methods This paper reviews the processes undertaken to research and develop a tool to bridge the data collection gap between the onset of a COVID-19 outbreak and the start of data collection using a prioritized electronic platform such as Go.Data in the WHO African Region. Results In anticipation of the implementation of a prioritized tool for field data collection, the DSV tool was deployed in 18 member states for COVID-19 outbreak data management. We highlight preliminary findings and lessons learned from the DSV tool deployment in the WHO African Region. Conclusions We developed a rapidly deployable tool for COVID-19 data collection and visualization in the WHO African Region. The lessons drawn on this experience offer an opportunity to learn and apply these to improve future similar public health informatics initiatives in an outbreak or similar humanitarian setting, particularly in low- and middle-income countries.

scholarly journals Novel Approach to Support Rapid Data Collection, Management, and Visualization During the COVID-19 Outbreak Response in the World Health Organization African Region: Development of a Data Summarization and Visualization Tool (Preprint)

2020 ◽  
Author(s):  
Kamran Ahmed ◽  
Muhammad Arish Bukhari ◽  
Tamayi Mlanda ◽  
Jean Paul Kimenyi ◽  
Polly Wallace ◽  
...  
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Field Data ◽  
World Health ◽  
African Region ◽  
Data Summarization ◽  
The World ◽  
Field Data Collection ◽  
Health Organization ◽  
Collection And Management

BACKGROUND The COVID-19 pandemic has created unprecedented challenges to the systematic and timely sharing of COVID-19 field data collection and management. The World Health Organization (WHO) is working with health partners on the rollout and implementation of a robust electronic field data collection platform. The delay in the deployment and rollout of this electronic platform in the WHO African Region, as a consequence of the application of large-scale public health and social measures including movement restrictions and geographical area quarantine, left a gap between data collection and management. This lead to the need to develop interim data management solutions to accurately monitor the evolution of the pandemic and support the deployment of appropriate public health interventions. OBJECTIVE The aim of this study is to review the design, development, and implementation of the COVID-19 Data Summarization and Visualization (DSV) tool as a rapidly deployable solution to fill this critical data collection gap as an interim solution. METHODS This paper reviews the processes undertaken to research and develop a tool to bridge the data collection gap between the onset of a COVID-19 outbreak and the start of data collection using a prioritized electronic platform such as Go.Data in the WHO African Region. RESULTS In anticipation of the implementation of a prioritized tool for field data collection, the DSV tool was deployed in 18 member states for COVID-19 outbreak data management. We highlight preliminary findings and lessons learned from the DSV tool deployment in the WHO African Region. CONCLUSIONS We developed a rapidly deployable tool for COVID-19 data collection and visualization in the WHO African Region. The lessons drawn on this experience offer an opportunity to learn and apply these to improve future similar public health informatics initiatives in an outbreak or similar humanitarian setting, particularly in low- and middle-income countries.

ADDITIONS TO STRABOSPOT FOR SEDIMENTARY FIELD DATA COLLECTION AND CONSTRUCTING STRATIGRAPHIC COLUMNS

2018 ◽  
Author(s):  
Casey J. Duncan ◽  
◽  
Marjorie A. Chan ◽  
Elizabeth Hajek ◽  
Diane L. Kamola ◽  
...  
Keyword(s):  
Data Collection ◽  
Field Data ◽  
Field Data Collection

Using digital data collection tools to improve overall cost-efficiency and provide timely analysis for decision making during invasive species eradication campaigns

2014 ◽  
Vol 41 (6) ◽  
pp. 499 ◽  
Author(s):  
David J. Will ◽  
Karl J. Campbell ◽  
Nick D. Holmes
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Cost Efficiency ◽  
Relational Databases ◽  
Cost Effective ◽  
Digital Data ◽  
Capital Costs ◽  
Project Costs ◽  
Time Required ◽  
Data Collection Effort

Context Worldwide, invasive vertebrate eradication campaigns are increasing in scale and complexity, requiring improved decision making tools to achieve and validate success. For managers of these campaigns, gaining access to timely summaries of field data can increase cost-efficiency and the likelihood of success, particularly for successive control-event style eradications. Conventional data collection techniques can be time intensive and burdensome to process. Recent advances in digital tools can reduce the time required to collect and process field information. Through timely analysis, efficiently collected data can inform decision making for managers both tactically, such as where to prioritise search effort, and strategically, such as when to transition from the eradication phase to confirmation monitoring. Aims We highlighted the advantages of using digital data collection tools, particularly the potential for reduced project costs through a decrease in effort and the ability to increase eradication efficiency by enabling explicit data-informed decision making. Methods We designed and utilised digital data collection tools, relational databases and a suite of analyses during two different eradication campaigns to inform management decisions: a feral cat eradication utilising trapping, and a rodent eradication using bait stations. Key results By using digital data collection during a 2-year long cat eradication, we experienced an 89% reduction in data collection effort and an estimated USD42 845 reduction in total costs compared with conventional paper methods. During a 2-month rodent bait station eradication, we experienced an 84% reduction in data collection effort and an estimated USD4525 increase in total costs. Conclusions Despite high initial capital costs, digital data collection systems provide increasing economics as the duration and scale of the campaign increases. Initial investments can be recouped by reusing equipment and software on subsequent projects, making digital data collection more cost-effective for programs contemplating multiple eradications. Implications With proper pre-planning, digital data collection systems can be integrated with quantitative models that generate timely forecasts of the effort required to remove all target animals and estimate the probability that eradication has been achieved to a desired level of confidence, thus improving decision making power and further reducing total project costs.

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